2 citations · 2 across the 1 of their papers we have counts for
4 papers
End-to-End Trainable Deep Active Contour Models for Automated Image Segmentation: Delineating Buildings in Aerial Imagery
Ali Hatamizadeh, Debleena Sengupta, Demetri Terzopoulos
The automated segmentation of buildings in remote sensing imagery is a challenging task that requires the accurate delineation of multiple building instances over typically large i…
End-to-End Deep Convolutional Active Contours for Image Segmentation
Ali Hatamizadeh, Debleena Sengupta, Demetri Terzopoulos
The Active Contour Model (ACM) is a standard image analysis technique whose numerous variants have attracted an enormous amount of research attention across multiple fields. Incorr…
Deep learning architectures for automated image segmentation
Debleena Sengupta
Image segmentation is widely used in a variety of computer vision tasks, such as object localization and recognition, boundary detection, and medical imaging. This thesis proposes…
Deep Active Lesion Segmentation
Ali Hatamizadeh, Assaf Hoogi, Debleena Sengupta +4
Lesion segmentation is an important problem in computer-assisted diagnosis that remains challenging due to the prevalence of low contrast, irregular boundaries that are unamenable…